Applications of artificial intelligence for disaster management
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …
socioeconomic loss. The actual damage and loss observed in the recent decades has …
[HTML][HTML] Reinforcement learning for humanitarian relief distribution with trucks and UAVs under travel time uncertainty
Effective humanitarian relief operations are challenging in the aftermath of disasters, as
trucks are often faced with considerable travel time uncertainties due to damaged …
trucks are often faced with considerable travel time uncertainties due to damaged …
Reinforcement learning approach for resource allocation in humanitarian logistics
When a disaster strikes, it is important to allocate limited disaster relief resources to those in
need. This paper considers the allocation of resources in humanitarian logistics using three …
need. This paper considers the allocation of resources in humanitarian logistics using three …
Approximate dynamic programming for network recovery problems with stochastic demand
Immediately after a disruption, in order to minimize the negative impact inflicted on the
society, its imperative to re-establish the interdicted critical services enabled by the …
society, its imperative to re-establish the interdicted critical services enabled by the …
A self-learning strategy for artificial cognitive control systems
G Beruvides, C Juanes, F Castaño… - 2015 IEEE 13th …, 2015 - ieeexplore.ieee.org
This paper presents a self-learning strategy for an artificial cognitive control based on a
reinforcement learning strategy, in particular, an on-line version of a Q-learning algorithm …
reinforcement learning strategy, in particular, an on-line version of a Q-learning algorithm …
[HTML][HTML] Road-reconstruction after multi-locational flooding in multi-agent deep RL with the consideration of human mobility-Case study: Western Japan flooding in …
S Joo, Y Ogawa, Y Sekimoto - International Journal of Disaster Risk …, 2022 - Elsevier
Record-breaking heavy rain occurred in Western Japan from June 28 to July 8, 2018. Many
roads in Hiroshima and Okayama Prefecture were disrupted simultaneously. The …
roads in Hiroshima and Okayama Prefecture were disrupted simultaneously. The …
Integrating estimation of distribution algorithms versus Q-learning into Meta-RaPS for solving the 0-1 multidimensional knapsack problem
Finding near-optimal solutions in an acceptable amount of time is a challenge when
developing sophisticated approximate approaches. A powerful answer to this challenge …
developing sophisticated approximate approaches. A powerful answer to this challenge …
[PDF][PDF] 基于非支配排序差异演化的应急资源多目标分配算法
苏兆品, 张国富, 蒋建国, 岳峰, 张婷 - 自动化学报, 2017 - aas.net.cn
摘要应急资源分配(Emergency resource allocation, ERA) 是灾害应急管理中的核心环节,
主要研究如何高效合理地把各储备点的应急救援物资分配给各发放点. 然而 …
主要研究如何高效合理地把各储备点的应急救援物资分配给各发放点. 然而 …
[HTML][HTML] Shortest path problem with arc failure scenarios
P Issac, AM Campbell - EURO Journal on Transportation and Logistics, 2017 - Elsevier
We consider a shortest path problem from source to destination over a set of arc failure
scenarios, considering the probability of different scenarios. A primary path is chosen, which …
scenarios, considering the probability of different scenarios. A primary path is chosen, which …
Intelligent decision system for responsive crisis management
MT Khouj, A Alsubaie, K Alutaibi… - … Journal of Critical …, 2018 - inderscienceonline.com
Disaster mitigation of severe catastrophic events depend heavily on effective decisions that
are made by officials. The goal of disaster management is to make decisions that properly …
are made by officials. The goal of disaster management is to make decisions that properly …